Pre-processing of the data

ls_preprocessed <- preprocess_rna(path_rnaseq = 'rnaseq.RData', correct_batch = T, correct_gender = T)

Exploring data

Batch effect correction

print(ls_preprocessed$pbatch_bf)

print(ls_preprocessed$pgender_bf)

print(ls_preprocessed$pbatch_af)

print(ls_preprocessed$pgender_af)

DE analysis

gn <- as.character(ls_preprocessed$rna_all$Feature[which(ls_preprocessed$rna_all$Feature_gene_name =='MT-CO1')])
DE_res <- DE_analysis(ls_preprocessed, 
           GeneBased=TRUE, 
           pDataBased=FALSE,
           NewCondition=FALSE,
           cond_nm= gn,
           reference = 'low', 
           correct_gender=TRUE,
           extremes_only=TRUE)
## Unlist done
## Labeling done
## Filtering done
## factor levels were dropped which had no samples
## Design done
## factor levels were dropped which had no samples
## Warning: Setting row names on a tibble is deprecated.
## vsd symbols done
## using pre-existing size factors
## estimating dispersions
## gene-wise dispersion estimates
## mean-dispersion relationship
## final dispersion estimates
## fitting model and testing
## -- replacing outliers and refitting for 1462 genes
## -- DESeq argument 'minReplicatesForReplace' = 7 
## -- original counts are preserved in counts(dds)
## estimating dispersions
## fitting model and testing
## DESeq done
## using 'normal' for LFC shrinkage, the Normal prior from Love et al (2014).
## 
## Note that type='apeglm' and type='ashr' have shown to have less bias than type='normal'.
## See ?lfcShrink for more details on shrinkage type, and the DESeq2 vignette.
## Reference: https://doi.org/10.1093/bioinformatics/bty895
## res symbols done
## list done

DE results

heatmap_200(DE_res$res_df, DE_res$vsd_mat_sym, DE_res$meta_data, DE_res$pData_rnaseq)

x <- DE_res$res_df %>%
  arrange(desc(abs(log2FoldChange)))
rownames(x) <- make.names(x$symbol, unique = T)
k <- gn
x <- x[-which(x$gene %in%k),]
#head(x, 10)
vp <- volcano_plot(x, gene=NULL, p_title='MT-CO1', pCutoff=0.001, FCcutoff=1.5)

List of genes differentially expressed (-1.5 > fold change > 1.5, pval<0.001)

vp_tb <- vp$data[which(vp$data$Sig == 'FC_P'),]
rownames(vp_tb) <- c(1:nrow(vp_tb))
kable(vp_tb)
baseMean log2FoldChange lfcSE stat pvalue padj gene symbol Sig lab xvals yvals
1.125816e+05 2.353824 0.2293886 10.335919 0.0000000 0.0000000 ENSG00000198938.2 MT-CO3 FC_P MT.CO3 2.353824 0.0000000
5.198489e+03 2.278406 0.2990219 7.574505 0.0000000 0.0000000 ENSG00000237973.1 hsa-mir-6723 FC_P hsa.mir.6723 2.278406 0.0000000
5.982732e+04 2.203564 0.2482062 8.994964 0.0000000 0.0000000 ENSG00000198899.2 MT-ATP6 FC_P MT.ATP6 2.203564 0.0000000
1.103602e+04 2.155337 0.2645491 8.361639 0.0000000 0.0000000 ENSG00000198840.2 MT-ND3 FC_P MT.ND3 2.155337 0.0000000
1.247616e+03 2.128188 0.2472266 8.728586 0.0000000 0.0000000 ENSG00000210196.2 MT-TP FC_P MT.TP 2.128188 0.0000000
8.698578e+04 2.062260 0.2484595 8.388171 0.0000000 0.0000000 ENSG00000198727.2 MT-CYB FC_P MT.CYB 2.062260 0.0000000
1.433006e+05 2.055945 0.2486033 8.404454 0.0000000 0.0000000 ENSG00000198886.2 MT-ND4 FC_P MT.ND4 2.055945 0.0000000
5.681042e+04 2.022377 0.2784002 7.406580 0.0000000 0.0000000 ENSG00000198763.3 MT-ND2 FC_P MT.ND2 2.022377 0.0000000
4.403830e+03 2.000968 0.2721310 7.461931 0.0000000 0.0000000 ENSG00000228253.1 MT-ATP8 FC_P MT.ATP8 2.000968 0.0000000
2.143278e+04 1.988149 0.2558639 7.863189 0.0000000 0.0000000 ENSG00000212907.2 MT-ND4L FC_P MT.ND4L 1.988149 0.0000000
7.148785e+04 1.968509 0.2600615 7.621205 0.0000000 0.0000000 ENSG00000198712.1 MT-CO2 FC_P MT.CO2 1.968509 0.0000000
6.830339e+03 1.936911 0.2729481 7.157711 0.0000000 0.0000000 ENSG00000248527.1 MTATP6P1 FC_P MTATP6P1 1.936911 0.0000000
1.514651e+02 1.924556 0.3419348 5.761648 0.0000000 0.0000146 ENSG00000134827.3 TCN1 FC_P TCN1 1.924556 0.0000000
3.312875e+01 1.898496 0.2765440 7.001108 0.0000000 0.0000000 ENSG00000198744.5 RP5-857K21.11 FC_P RP5.857K21.11 1.898496 0.0000000
1.968497e+01 1.874076 0.3133995 6.212204 0.0000000 0.0000010 ENSG00000262902.1 RP11-750B16.1 FC_P RP11.750B16.1 1.874076 0.0000000
7.322624e+04 1.859089 0.2487022 7.533098 0.0000000 0.0000000 ENSG00000198888.2 MT-ND1 FC_P MT.ND1 1.859089 0.0000000
1.059623e+05 1.796863 0.2323919 7.795807 0.0000000 0.0000000 ENSG00000198786.2 MT-ND5 FC_P MT.ND5 1.796863 0.0000000
8.927144e+00 1.785540 0.3370058 4.744627 0.0000021 0.0013212 ENSG00000213759.4 UGT2B11 FC_P UGT2B11 1.785540 0.0000021
2.125741e+02 1.764552 0.3231629 5.192940 0.0000002 0.0002547 ENSG00000091137.7 SLC26A4 FC_P SLC26A4 1.764552 0.0000002
2.170370e+01 1.712493 0.3402747 5.267992 0.0000001 0.0001833 ENSG00000250748.2 RP11-230G5.2 FC_P RP11.230G5.2 1.712493 0.0000001
4.747433e+01 1.671178 0.3050743 5.625947 0.0000000 0.0000292 ENSG00000229344.1 RP5-857K21.7 FC_P RP5.857K21.7 1.671178 0.0000000
2.090561e+04 1.670813 0.2476740 6.787578 0.0000000 0.0000000 ENSG00000198695.2 MT-ND6 FC_P MT.ND6 1.670813 0.0000000
1.624918e+01 1.647497 0.3433486 5.307120 0.0000001 0.0001542 ENSG00000139151.10 PLCZ1 FC_P PLCZ1 1.647497 0.0000001
3.527544e+00 1.611987 0.3450183 5.019375 0.0000005 NA ENSG00000255892.1 RP11-459D22.2 FC_P RP11.459D22.2 1.611987 0.0000005
6.197128e+00 1.599341 0.3374953 4.618169 0.0000039 0.0019283 ENSG00000225294.1 OSTCP2 FC_P OSTCP2 1.599341 0.0000039
9.915782e+01 1.595427 0.3334509 5.185725 0.0000002 0.0002548 ENSG00000139144.5 PIK3C2G FC_P PIK3C2G 1.595427 0.0000002
3.501089e+01 1.533833 0.3180315 3.300269 0.0009659 0.0309132 ENSG00000147003.5 TMEM27 FC_P TMEM27 1.533833 0.0009659
4.345090e+02 1.523048 0.3399692 4.739014 0.0000021 0.0013212 ENSG00000197301.3 RP11-366L20.2 FC_P RP11.366L20.2 1.523048 0.0000021
3.706270e+00 -1.500648 0.3370660 -4.036736 0.0000542 NA ENSG00000104938.12 CLEC4M FC_P CLEC4M -1.500648 0.0000542

Pathway enrichment analysis fGSEA

Low MT-CO1 is the reference. When MT-CO1 is high, pathways shown below are up- or down- regulated

fgsea_res <- fgsea_analysis(DE_res)
## `summarise()` ungrouping output (override with `.groups` argument)
## Warning in fgsea(pathways = gmtPathways(pthw_path), stats = ranks, nperm = 1000): There are ties in the preranked stats (0.02% of the list).
## The order of those tied genes will be arbitrary, which may produce unexpected results.

## Warning in fgsea(pathways = gmtPathways(pthw_path), stats = ranks, nperm = 1000): There are ties in the preranked stats (0.02% of the list).
## The order of those tied genes will be arbitrary, which may produce unexpected results.

## Warning in fgsea(pathways = gmtPathways(pthw_path), stats = ranks, nperm = 1000): There are ties in the preranked stats (0.02% of the list).
## The order of those tied genes will be arbitrary, which may produce unexpected results.

## Warning in fgsea(pathways = gmtPathways(pthw_path), stats = ranks, nperm = 1000): There are ties in the preranked stats (0.02% of the list).
## The order of those tied genes will be arbitrary, which may produce unexpected results.

## Warning in fgsea(pathways = gmtPathways(pthw_path), stats = ranks, nperm = 1000): There are ties in the preranked stats (0.02% of the list).
## The order of those tied genes will be arbitrary, which may produce unexpected results.

## Warning in fgsea(pathways = gmtPathways(pthw_path), stats = ranks, nperm = 1000): There are ties in the preranked stats (0.02% of the list).
## The order of those tied genes will be arbitrary, which may produce unexpected results.

## Warning in fgsea(pathways = gmtPathways(pthw_path), stats = ranks, nperm = 1000): There are ties in the preranked stats (0.02% of the list).
## The order of those tied genes will be arbitrary, which may produce unexpected results.

## Warning in fgsea(pathways = gmtPathways(pthw_path), stats = ranks, nperm = 1000): There are ties in the preranked stats (0.02% of the list).
## The order of those tied genes will be arbitrary, which may produce unexpected results.

## Warning in fgsea(pathways = gmtPathways(pthw_path), stats = ranks, nperm = 1000): There are ties in the preranked stats (0.02% of the list).
## The order of those tied genes will be arbitrary, which may produce unexpected results.
fgp <- fgsea_plot(fgsea_res$res_hm, pathways_title='Hallmark', condition_name='MT-CO1 low vs high')

kable(fgp)
pathway pval padj ES NES nMoreExtreme size state
HALLMARK_INFLAMMATORY_RESPONSE 0.0035211 0.0100281 -0.5166999 -2.728497 0 193 down
HALLMARK_TNFA_SIGNALING_VIA_NFKB 0.0036101 0.0100281 -0.5024724 -2.647208 0 195 down
HALLMARK_INTERFERON_GAMMA_RESPONSE 0.0036101 0.0100281 -0.4971237 -2.615423 0 194 down
HALLMARK_MYOGENESIS 0.0035461 0.0100281 -0.4898842 -2.576125 0 190 down
HALLMARK_IL6_JAK_STAT3_SIGNALING 0.0029155 0.0100281 -0.5502704 -2.476286 0 82 down
HALLMARK_INTERFERON_ALPHA_RESPONSE 0.0029762 0.0100281 -0.5259010 -2.439549 0 93 down
HALLMARK_ALLOGRAFT_REJECTION 0.0035461 0.0100281 -0.4508472 -2.364764 0 187 down
HALLMARK_APOPTOSIS 0.0032787 0.0100281 -0.4370195 -2.215322 0 155 down
HALLMARK_UV_RESPONSE_UP 0.0031250 0.0100281 -0.4358901 -2.192390 0 147 down
HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION 0.0035211 0.0100281 -0.3777047 -1.986254 0 189 down
HALLMARK_APICAL_JUNCTION 0.0035211 0.0100281 -0.3765949 -1.980417 0 189 down
HALLMARK_IL2_STAT5_SIGNALING 0.0035461 0.0100281 -0.3710633 -1.951289 0 190 down
HALLMARK_PROTEIN_SECRETION 0.0015198 0.0100281 0.4567544 1.926923 0 89 up
HALLMARK_P53_PATHWAY 0.0035461 0.0100281 -0.3652752 -1.920851 0 190 down
HALLMARK_COMPLEMENT 0.0035211 0.0100281 -0.3611703 -1.907204 0 193 down
HALLMARK_COAGULATION 0.0031153 0.0100281 -0.3748569 -1.841698 0 127 down
HALLMARK_REACTIVE_OXYGEN_SPECIES_PATHWAY 0.0025641 0.0100281 -0.4586332 -1.801411 0 46 down
HALLMARK_XENOBIOTIC_METABOLISM 0.0035461 0.0100281 -0.3365890 -1.768958 0 188 down
HALLMARK_ADIPOGENESIS 0.0069444 0.0156961 -0.3218566 -1.681588 1 183 down
HALLMARK_HYPOXIA 0.0069444 0.0156961 -0.3181967 -1.656740 1 180 down
HALLMARK_MITOTIC_SPINDLE 0.0072202 0.0156961 -0.2773518 -1.461190 1 195 down
HALLMARK_KRAS_SIGNALING_DN 0.0070922 0.0156961 -0.2735489 -1.416369 1 179 down
HALLMARK_HEME_METABOLISM 0.0070922 0.0156961 -0.2691462 -1.393572 1 179 down
HALLMARK_APICAL_SURFACE 0.0079156 0.0164908 -0.4383320 -1.674993 2 42 down
HALLMARK_PI3K_AKT_MTOR_SIGNALING 0.0084986 0.0169972 -0.3378296 -1.607182 2 103 down
HALLMARK_ESTROGEN_RESPONSE_LATE 0.0105634 0.0203142 -0.2599879 -1.372898 2 193 down
HALLMARK_MYC_TARGETS_V2 0.0168539 0.0312110 -0.3992977 -1.659281 5 57 down
HALLMARK_ANGIOGENESIS 0.0203046 0.0362582 -0.4297947 -1.582696 7 35 down
HALLMARK_G2M_CHECKPOINT 0.0248227 0.0427978 -0.2469708 -1.295400 6 187 down 
fgp <- fgsea_plot(fgsea_res$res_c1, pathways_title='C1 positional genes', condition_name='MT-CO1 low vs high')

kable(fgp)
pathway pval padj ES NES nMoreExtreme size state
MT 0.0017065 0.0101893 0.9033591 3.128845 0 31 up
chr14q22 0.0016026 0.0101893 0.6781614 2.733202 0 62 up
chr14q23 0.0015873 0.0101893 0.6359824 2.643019 0 77 up
chr14q21 0.0015748 0.0101893 0.6835410 2.632522 0 50 up
chr7p21 0.0016502 0.0101893 0.6988657 2.599868 0 45 up
chr6q14 0.0015873 0.0101893 0.6602270 2.532750 0 49 up
chr8q22 0.0015528 0.0101893 0.5695323 2.399848 0 84 up
chr12p12 0.0015848 0.0101893 0.5709453 2.321493 0 65 up
chr5q13 0.0016026 0.0101893 0.5612406 2.299213 0 70 up
chr6q16 0.0017065 0.0101893 0.6631502 2.296866 0 31 up
chr12q15 0.0017212 0.0101893 0.6511415 2.293115 0 34 up
chr1q41 0.0015873 0.0101893 0.5960861 2.286694 0 49 up
chr12p11 0.0016502 0.0101893 0.6203476 2.266348 0 41 up
chr5q15 0.0016287 0.0101893 0.6227980 2.248737 0 37 up
chr14q13 0.0016529 0.0101893 0.5958189 2.200769 0 44 up
chr10q21 0.0016051 0.0101893 0.5444881 2.200221 0 64 up
chr2q31 0.0015221 0.0101893 0.5062130 2.171557 0 94 up
chr3q26 0.0014556 0.0101893 0.4923513 2.166231 0 104 up
chr12q14 0.0015924 0.0101893 0.5480686 2.152203 0 55 up
chr5q14 0.0016026 0.0101893 0.5189769 2.126073 0 70 up
chr8q21 0.0015106 0.0101893 0.4948910 2.121953 0 90 up
chr7p14 0.0014903 0.0101893 0.4830610 2.121799 0 107 up
chr5q11 0.0016502 0.0101893 0.5692116 2.117538 0 45 up
chr1p21 0.0015748 0.0101893 0.5476311 2.109092 0 50 up
chr1q43 0.0016807 0.0101893 0.6011915 2.070108 0 29 up
chr1p31 0.0014347 0.0101893 0.4573857 2.059690 0 120 up
chr11q14 0.0015723 0.0101893 0.4908436 2.043308 0 76 up
chr15q14 0.0016584 0.0101893 0.5701549 2.039194 0 35 up
chr5q12 0.0016207 0.0101893 0.5575577 2.028013 0 39 up
chr5q22 0.0016474 0.0101893 0.5551921 2.013379 0 38 up 
fgp <- fgsea_plot(fgsea_res$res_c2, pathways_title='C2 curated genes', condition_name='MT-CO1 low vs high')

kable(fgp)
pathway pval padj ES NES nMoreExtreme size state
SHEN_SMARCA2_TARGETS_UP 0.0012346 0.0230991 0.6214452 3.185662 0 407 up
MILI_PSEUDOPODIA_HAPTOTAXIS_UP 0.0012180 0.0230991 0.6094541 3.151499 0 469 up
SENGUPTA_EBNA1_ANTICORRELATED 0.0034247 0.0230991 -0.6104509 -2.999846 0 132 down
QI_PLASMACYTOMA_UP 0.0037736 0.0230991 -0.5389177 -2.907804 0 243 down
TONKS_TARGETS_OF_RUNX1_RUNX1T1_FUSION_HSC_DN 0.0034483 0.0230991 -0.5585107 -2.875797 0 177 down
BASSO_CD40_SIGNALING_UP 0.0031348 0.0230991 -0.6003008 -2.843502 0 100 down
DIRMEIER_LMP1_RESPONSE_EARLY 0.0028090 0.0230991 -0.6496554 -2.838583 0 62 down
NIKOLSKY_BREAST_CANCER_16P13_AMPLICON 0.0031646 0.0230991 -0.5964448 -2.831300 0 105 down
FAELT_B_CLL_WITH_VH3_21_UP 0.0025907 0.0230991 -0.6900536 -2.775154 0 41 down
DIRMEIER_LMP1_RESPONSE_LATE_UP 0.0025707 0.0230991 -0.6595436 -2.763610 0 49 down
HAMAI_APOPTOSIS_VIA_TRAIL_DN 0.0035088 0.0230991 -0.5321489 -2.754696 0 184 down
KIM_ALL_DISORDERS_DURATION_CORR_DN 0.0034483 0.0230991 -0.5573907 -2.751626 0 134 down
MIKKELSEN_ES_LCP_WITH_H3K4ME3 0.0033003 0.0230991 -0.5555379 -2.731132 0 127 down
BROWNE_INTERFERON_RESPONSIVE_GENES 0.0028818 0.0230991 -0.6095979 -2.707059 0 65 down
HAMAI_APOPTOSIS_VIA_TRAIL_UP 0.0011848 0.0230991 0.5114199 2.699999 0 609 up
NIKOLSKY_BREAST_CANCER_16Q24_AMPLICON 0.0025974 0.0230991 -0.6331548 -2.680007 0 51 down
PARK_TRETINOIN_RESPONSE_AND_PML_RARA_FUSION 0.0025126 0.0230991 -0.7060619 -2.659373 0 29 down
MULLIGHAN_NPM1_MUTATED_SIGNATURE_2_DN 0.0028736 0.0230991 -0.5888260 -2.651392 0 69 down
ALTEMEIER_RESPONSE_TO_LPS_WITH_MECHANICAL_VENTILATION 0.0032051 0.0230991 -0.5468294 -2.650769 0 118 down
REACTOME_IMMUNOREGULATORY_INTERACTIONS_BETWEEN_A_LYMPHOID_AND_A_NON_LYMPHOID_CELL 0.0035842 0.0230991 -0.5185094 -2.647499 0 175 down
ZHANG_BREAST_CANCER_PROGENITORS_UP 0.0012346 0.0230991 0.5148286 2.639123 0 407 up
GABRIELY_MIR21_TARGETS 0.0013123 0.0230991 0.5283675 2.633530 0 271 up
LIN_APC_TARGETS 0.0029326 0.0230991 -0.5987343 -2.632837 0 64 down
KASLER_HDAC7_TARGETS_1_UP 0.0037736 0.0230991 -0.5180264 -2.617063 0 168 down
VILIMAS_NOTCH1_TARGETS_DN 0.0025381 0.0230991 -0.7502278 -2.615992 0 22 down
AMIT_EGF_RESPONSE_480_HELA 0.0036765 0.0230991 -0.5199181 -2.596965 0 151 down
REACTOME_INTERFERON_ALPHA_BETA_SIGNALING 0.0027624 0.0230991 -0.5996013 -2.590248 0 58 down
NIKOLSKY_BREAST_CANCER_8Q12_Q22_AMPLICON 0.0014245 0.0230991 0.5807377 2.589905 0 122 up
VERHAAK_GLIOBLASTOMA_MESENCHYMAL 0.0037879 0.0230991 -0.4963387 -2.587929 0 210 down
FLECHNER_BIOPSY_KIDNEY_TRANSPLANT_REJECTED_VS_OK_UP 0.0030488 0.0230991 -0.5622852 -2.577966 0 83 down 
fgp <- fgsea_plot(fgsea_res$res_c3, pathways_title='C3 regulatory target genes', condition_name='MT-CO1 low vs high')

kable(fgp)
pathway pval padj ES NES nMoreExtreme size state
MIR607 0.0011261 0.0071782 0.4944853 2.679493 0 906 up
MIR576_5P 0.0012755 0.0071782 0.5301651 2.649113 0 315 up
MIR4799_5P 0.0012346 0.0071782 0.5115993 2.611655 0 374 up
MIR3646 0.0011561 0.0071782 0.4803730 2.580658 0 797 up
HJURP_TARGET_GENES 0.0015723 0.0071782 0.6682548 2.574568 0 51 up
MIR7_2_3P 0.0011751 0.0071782 0.4867135 2.573177 0 617 up
MIR1250_3P 0.0012210 0.0071782 0.4936121 2.565582 0 464 up
MIR3606_3P 0.0012610 0.0071782 0.5098986 2.564927 0 332 up
MIR513A_3P_MIR513C_3P 0.0012392 0.0071782 0.4995638 2.564281 0 411 up
MIR6074 0.0013263 0.0071782 0.5216858 2.558826 0 251 up
MIR541_5P 0.0014577 0.0071782 0.5844128 2.558138 0 111 up
MIR7_1_3P 0.0011792 0.0071782 0.4840289 2.557208 0 619 up
MIR7856_5P 0.0012392 0.0071782 0.5002219 2.551287 0 376 up
MIR3662 0.0011351 0.0071782 0.4710273 2.548929 0 897 up
MIR8063 0.0012422 0.0071782 0.4993343 2.545229 0 371 up
MIR302C_5P 0.0011862 0.0071782 0.4805012 2.526993 0 540 up
MIR3671 0.0011655 0.0071782 0.4765459 2.519081 0 596 up
MIR380_3P 0.0013587 0.0071782 0.5223945 2.518560 0 217 up
MIR186_5P 0.0011962 0.0071782 0.4780738 2.507776 0 529 up
MIR548AE_3P_MIR548AQ_3P 0.0011628 0.0071782 0.4683896 2.504792 0 737 up
MIR3133 0.0012285 0.0071782 0.4810222 2.498855 0 472 up
MIR548J_3P 0.0011723 0.0071782 0.4679042 2.498530 0 734 up
MIR12124 0.0012837 0.0071782 0.4995472 2.484906 0 303 up
MIR548AH_3P_MIR548AM_3P 0.0011710 0.0071782 0.4650212 2.483253 0 733 up
MIR548N 0.0011792 0.0071782 0.4699310 2.473825 0 568 up
MIR32_3P 0.0012788 0.0071782 0.4960537 2.471391 0 310 up
MIR3143 0.0012361 0.0071782 0.4776853 2.465106 0 430 up
MIR34C_3P 0.0015723 0.0071782 0.6228463 2.461628 0 62 up
MIR548AJ_3P_MIR548X_3P 0.0011325 0.0071782 0.4528336 2.446967 0 853 up
MIR4680_3P 0.0013441 0.0071782 0.5023971 2.443385 0 239 up 
fgp <- fgsea_plot(fgsea_res$res_c4, pathways_title='C4 cancer', condition_name='MT-CO1 low vs high')

kable(fgp)
pathway pval padj ES NES nMoreExtreme size state
GNF2_ITGB2 0.0025126 0.0156526 -0.6911401 -2.895633 0 51 down
GNF2_TNFRSF1B 0.0025445 0.0156526 -0.6519754 -2.855359 0 59 down
GNF2_S100A4 0.0024331 0.0156526 -0.6957840 -2.778754 0 44 down
GNF2_FGR 0.0024390 0.0156526 -0.7620046 -2.769924 0 30 down
GNF2_IL2RB 0.0025381 0.0156526 -0.7025898 -2.684422 0 37 down
MODULE_430 0.0026178 0.0156526 -0.6316267 -2.682751 0 54 down
MODULE_257 0.0033223 0.0156526 -0.5271417 -2.669231 0 150 down
MODULE_241 0.0028249 0.0156526 -0.5840829 -2.636794 0 70 down
GNF2_PTPN4 0.0024331 0.0156526 -0.6549595 -2.615714 0 44 down
MODULE_174 0.0030211 0.0156526 -0.5507038 -2.576494 0 92 down
GNF2_CASP1 0.0030211 0.0156526 -0.5320882 -2.559521 0 103 down
GNF2_CD7 0.0025000 0.0156526 -0.6599203 -2.504273 0 36 down
MODULE_291 0.0026954 0.0156526 -0.5727886 -2.500499 0 62 down
MODULE_79 0.0030030 0.0156526 -0.5324167 -2.499789 0 95 down
MODULE_128 0.0030030 0.0156526 -0.5331226 -2.496941 0 93 down
GNF2_HCK 0.0031348 0.0156526 -0.5363299 -2.483143 0 89 down
GNF2_RAB7L1 0.0024390 0.0156526 -0.6790360 -2.468329 0 30 down
MODULE_484 0.0024213 0.0156526 -0.6282085 -2.468025 0 41 down
GNF2_MYD88 0.0026042 0.0156526 -0.5768283 -2.467434 0 55 down
MODULE_170 0.0030030 0.0156526 -0.5216000 -2.449002 0 95 down
GNF2_PECAM1 0.0025575 0.0156526 -0.5708076 -2.422301 0 53 down
MODULE_20 0.0029326 0.0156526 -0.5342236 -2.405219 0 74 down
GNF2_CYP2B6 0.0024752 0.0156526 -0.5935187 -2.400250 0 46 down
GNF2_MATK 0.0023981 0.0156526 -0.6969473 -2.400119 0 24 down
MORF_PML 0.0031546 0.0156526 -0.4810702 -2.388631 0 131 down
MORF_ARAF1 0.0029499 0.0156526 -0.5305289 -2.379562 0 73 down
GNF2_CARD15 0.0027548 0.0156526 -0.5392377 -2.377421 0 65 down
MORF_GPX4 0.0024938 0.0156526 -0.5697568 -2.371449 0 50 down
GNF2_HLA_C 0.0024213 0.0156526 -0.6034493 -2.370755 0 41 down
MODULE_350 0.0026178 0.0156526 -0.5465875 -2.358469 0 57 down 
fgp <- fgsea_plot(fgsea_res$res_c5, pathways_title='C5 GO genes', condition_name='MT-CO1 low vs high')

kable(fgp)
pathway pval padj ES NES nMoreExtreme size state
GO_ALPHA_BETA_T_CELL_ACTIVATION 0.0031348 0.0414217 -0.5193727 -2.518853 0 131 down
GO_T_CELL_DIFFERENTIATION 0.0037879 0.0414217 -0.4683992 -2.480167 0 233 down
GO_POSITIVE_REGULATION_OF_CELL_ACTIVATION 0.0046083 0.0414217 -0.4402180 -2.455196 0 355 down
GO_NEGATIVE_REGULATION_OF_CYTOKINE_PRODUCTION_INVOLVED_IN_IMMUNE_RESPONSE 0.0023310 0.0414217 -0.7119093 -2.445444 0 23 down
GO_LYMPHOCYTE_DIFFERENTIATION 0.0043668 0.0414217 -0.4381459 -2.430159 0 327 down
GO_T_CELL_RECEPTOR_COMPLEX 0.0028329 0.0414217 -0.5344270 -2.422824 0 90 down
GO_POSITIVE_REGULATION_OF_INTERLEUKIN_4_PRODUCTION 0.0023148 0.0414217 -0.7074415 -2.409413 0 22 down
GO_REGULATION_OF_T_CELL_ACTIVATION 0.0042017 0.0414217 -0.4356865 -2.392107 0 303 down
GO_REGULATION_OF_ANTIGEN_PROCESSING_AND_PRESENTATION 0.0022936 0.0414217 -0.7333934 -2.391422 0 19 down
GO_ALPHA_BETA_T_CELL_DIFFERENTIATION 0.0029070 0.0414217 -0.5228599 -2.386759 0 98 down
GO_REGULATION_OF_INFLAMMATORY_RESPONSE 0.0043668 0.0414217 -0.4299698 -2.384810 0 327 down
GO_LEUKOCYTE_PROLIFERATION 0.0040323 0.0414217 -0.4400706 -2.378877 0 275 down
GO_NEGATIVE_REGULATION_OF_INFLAMMATORY_RESPONSE 0.0033003 0.0414217 -0.4894358 -2.378345 0 140 down
GO_RESPIRASOME 0.0015314 0.0414217 0.5564150 2.373546 0 88 up
GO_NEGATIVE_REGULATION_OF_INTERLEUKIN_6_PRODUCTION 0.0026385 0.0414217 -0.5860676 -2.372996 0 49 down
GO_LEUKOCYTE_CELL_CELL_ADHESION 0.0045249 0.0414217 -0.4299917 -2.369350 0 320 down
GO_STEROID_CATABOLIC_PROCESS 0.0023866 0.0414217 -0.6695197 -2.367841 0 25 down
GO_PROTEIN_LIPID_COMPLEX_BINDING 0.0025253 0.0414217 -0.6496216 -2.364210 0 29 down
GO_REGULATION_OF_IMMUNE_EFFECTOR_PROCESS 0.0046948 0.0414217 -0.4163965 -2.360824 0 420 down
GO_NEGATIVE_REGULATION_OF_DEFENSE_RESPONSE 0.0035211 0.0414217 -0.4513739 -2.360095 0 206 down
GO_POSITIVE_REGULATION_OF_LEUKOCYTE_CELL_CELL_ADHESION 0.0036630 0.0414217 -0.4522428 -2.357548 0 209 down
GO_REGULATION_OF_PRODUCTION_OF_MOLECULAR_MEDIATOR_OF_IMMUNE_RESPONSE 0.0031348 0.0414217 -0.4843216 -2.348863 0 131 down
GO_ATP_SYNTHESIS_COUPLED_ELECTRON_TRANSPORT 0.0015314 0.0414217 0.5498380 2.345490 0 88 up
GO_NADH_DEHYDROGENASE_ACTIVITY 0.0016556 0.0414217 0.6345283 2.341045 0 44 up
GO_POSITIVE_REGULATION_OF_ERK1_AND_ERK2_CASCADE 0.0034247 0.0414217 -0.4523257 -2.333569 0 188 down
GO_RESPONSE_TO_PEPTIDOGLYCAN 0.0022472 0.0414217 -0.8702731 -2.333207 0 10 down
GO_CELLULAR_RESPONSE_TO_BIOTIC_STIMULUS 0.0037175 0.0414217 -0.4445874 -2.331516 0 219 down
GO_REGULATION_OF_NEUTROPHIL_ACTIVATION 0.0022676 0.0414217 -0.8414661 -2.326205 0 11 down
GO_INTEGRIN_MEDIATED_SIGNALING_PATHWAY 0.0028902 0.0414217 -0.5085460 -2.323330 0 97 down
GO_SYNCYTIUM_FORMATION 0.0026178 0.0414217 -0.5681441 -2.319278 0 50 down 
fgp <- fgsea_plot(fgsea_res$res_c6, pathways_title='C6 oncogenic', condition_name='MT-CO1 low vs high')

kable(fgp)
pathway pval padj ES NES nMoreExtreme size state
PRC2_EED_UP.V1_DN 0.0033670 0.0097609 -0.5424789 -2.792733 0 179 down
CYCLIN_D1_UP.V1_UP 0.0034014 0.0097609 -0.5217470 -2.660610 0 173 down
PIGF_UP.V1_UP 0.0014124 0.0097609 0.5215918 2.460068 0 181 up
PDGF_ERK_DN.V1_DN 0.0032362 0.0097609 -0.4943174 -2.439401 0 141 down
ATF2_UP.V1_UP 0.0032362 0.0097609 -0.4745666 -2.421739 0 165 down
RAPA_EARLY_UP.V1_DN 0.0033670 0.0097609 -0.4735251 -2.411170 0 167 down
IL15_UP.V1_UP 0.0033898 0.0097609 -0.4445118 -2.269528 0 174 down
VEGF_A_UP.V1_UP 0.0034130 0.0097609 -0.4387310 -2.238506 0 177 down
PIGF_UP.V1_DN 0.0033670 0.0097609 -0.4338658 -2.215623 0 169 down
TBK1.DF_DN 0.0013369 0.0097609 0.4449224 2.212234 0 265 up
SRC_UP.V1_UP 0.0032895 0.0097609 -0.4438094 -2.204890 0 148 down
HINATA_NFKB_IMMU_INF 0.0022676 0.0097609 -0.7483708 -2.163509 0 14 down
BMI1_DN_MEL18_DN.V1_UP 0.0033445 0.0097609 -0.4386359 -2.143131 0 135 down
CYCLIN_D1_KE_.V1_UP 0.0034130 0.0097609 -0.4154743 -2.127258 0 178 down
IL2_UP.V1_UP 0.0033557 0.0097609 -0.4142684 -2.112426 0 170 down
MEL18_DN.V1_UP 0.0032680 0.0097609 -0.4366196 -2.106819 0 129 down
RAPA_EARLY_UP.V1_UP 0.0031949 0.0097609 -0.4213389 -2.095798 0 146 down
RB_P107_DN.V1_UP 0.0033113 0.0097609 -0.4307204 -2.073399 0 128 down
GCNP_SHH_UP_LATE.V1_DN 0.0033670 0.0097609 -0.4054377 -2.064472 0 167 down
ERBB2_UP.V1_DN 0.0014085 0.0097609 0.4361698 2.058619 0 182 up
BMI1_DN.V1_UP 0.0033557 0.0097609 -0.4226519 -2.047233 0 133 down
ALK_DN.V1_UP 0.0033113 0.0097609 -0.4258265 -2.030372 0 124 down
CSR_LATE_UP.V1_DN 0.0033113 0.0097609 -0.4124100 -1.995100 0 130 down
ATF2_S_UP.V1_DN 0.0033557 0.0097609 -0.3903671 -1.994436 0 172 down
LEF1_UP.V1_UP 0.0033670 0.0097609 -0.3855136 -1.984660 0 179 down
KRAS.AMP.LUNG_UP.V1_DN 0.0032258 0.0097609 -0.4128406 -1.970052 0 120 down
RB_DN.V1_UP 0.0033113 0.0097609 -0.4141831 -1.967801 0 123 down
ESC_V6.5_UP_EARLY.V1_DN 0.0033670 0.0097609 -0.3883519 -1.936019 0 152 down
SNF5_DN.V1_UP 0.0033670 0.0097609 -0.3857501 -1.923048 0 152 down
RB_P130_DN.V1_UP 0.0031447 0.0097609 -0.4024186 -1.914111 0 114 down 
fgp <- fgsea_plot(fgsea_res$res_c7, pathways_title='C7 immunologic', condition_name='MT-CO1 low vs high')

kable(fgp)
pathway pval padj ES NES nMoreExtreme size state
GSE369_PRE_VS_POST_IL6_INJECTION_SOCS3_KO_LIVER_DN 0.0036630 0.0089815 -0.6451392 -3.350586 0 187 down
GSE9988_LPS_VS_VEHICLE_TREATED_MONOCYTE_DN 0.0036232 0.0089815 -0.6071365 -3.172598 0 191 down
GSE9988_ANTI_TREM1_AND_LPS_VS_VEHICLE_TREATED_MONOCYTES_DN 0.0035842 0.0089815 -0.6003589 -3.127074 0 189 down
GSE9006_TYPE_1_VS_TYPE_2_DIABETES_PBMC_AT_DX_UP 0.0036630 0.0089815 -0.6005153 -3.118827 0 187 down
GSE9601_UNTREATED_VS_PI3K_INHIBITOR_TREATED_HCMV_INF_MONOCYTE_UP 0.0036232 0.0089815 -0.6029732 -3.091378 0 162 down
GSE9988_ANTI_TREM1_VS_VEHICLE_TREATED_MONOCYTES_DN 0.0035971 0.0089815 -0.5900630 -3.083918 0 190 down
GSE36527_CD69_NEG_VS_POS_TREG_CD62L_LOS_KLRG1_NEG_DN 0.0035587 0.0089815 -0.5691509 -2.958206 0 183 down
GSE6269_HEALTHY_VS_FLU_INF_PBMC_DN 0.0033898 0.0089815 -0.5834221 -2.956426 0 148 down
GSE16385_MONOCYTE_VS_12H_IL4_TREATED_MACROPHAGE_DN 0.0035587 0.0089815 -0.5674304 -2.949263 0 183 down
GSE27670_BLIMP1_VS_LMP1_TRANSDUCED_GC_BCELL_UP 0.0035587 0.0089815 -0.5618871 -2.920451 0 183 down
GSE360_L_DONOVANI_VS_B_MALAYI_HIGH_DOSE_MAC_DN 0.0035461 0.0089815 -0.5614279 -2.919446 0 184 down
GSE10325_LUPUS_BCELL_VS_LUPUS_MYELOID_DN 0.0034965 0.0089815 -0.5549483 -2.912236 0 192 down
GSE360_DC_VS_MAC_B_MALAYI_HIGH_DOSE_DN 0.0035461 0.0089815 -0.5595859 -2.909867 0 184 down
GSE7218_UNSTIM_VS_ANTIGEN_STIM_THROUGH_IGG_BCELL_DN 0.0035714 0.0089815 -0.5660759 -2.898726 0 159 down
GSE22140_HEALTHY_VS_ARTHRITIC_GERMFREE_MOUSE_CD4_TCELL_DN 0.0036232 0.0089815 -0.5534128 -2.891865 0 191 down
GSE9006_HEALTHY_VS_TYPE_2_DIABETES_PBMC_AT_DX_UP 0.0034965 0.0089815 -0.5568072 -2.891208 0 181 down
GSE10325_BCELL_VS_MYELOID_DN 0.0035587 0.0089815 -0.5549508 -2.884399 0 183 down
GSE23568_CTRL_TRANSDUCED_VS_WT_CD8_TCELL_DN 0.0036101 0.0089815 -0.5521093 -2.872602 0 188 down
GSE24634_TREG_VS_TCONV_POST_DAY10_IL4_CONVERSION_DN 0.0036101 0.0089815 -0.5485671 -2.854171 0 188 down
GSE7460_TREG_VS_TCONV_ACT_WITH_TGFB_DN 0.0035461 0.0089815 -0.5471283 -2.827283 0 176 down
GSE10325_LUPUS_CD4_TCELL_VS_LUPUS_MYELOID_DN 0.0036630 0.0089815 -0.5431416 -2.822144 0 186 down
GSE360_HIGH_DOSE_B_MALAYI_VS_M_TUBERCULOSIS_MAC_UP 0.0036630 0.0089815 -0.5382570 -2.795484 0 187 down
GSE5099_UNSTIM_VS_MCSF_TREATED_MONOCYTE_DAY3_DN 0.0036101 0.0089815 -0.5368805 -2.793366 0 188 down
GSE28726_NAIVE_CD4_TCELL_VS_NAIVE_NKTCELL_DN 0.0036630 0.0089815 -0.5329758 -2.769323 0 186 down
GSE9988_LOW_LPS_VS_VEHICLE_TREATED_MONOCYTE_DN 0.0035971 0.0089815 -0.5276631 -2.757790 0 190 down
GSE3337_CTRL_VS_16H_IFNG_IN_CD8POS_DC_DN 0.0034483 0.0089815 -0.5296092 -2.757252 0 180 down
GSE13485_DAY1_VS_DAY21_YF17D_VACCINE_PBMC_DN 0.0013889 0.0089815 0.5829842 2.748039 0 176 up
GSE44649_NAIVE_VS_ACTIVATED_CD8_TCELL_MIR155_KO_DN 0.0013736 0.0089815 0.5747852 2.726770 0 185 up
GSE32986_CURDLAN_HIGHDOSE_VS_GMCSF_AND_CURDLAN_HIGHDOSE_STIM_DC_DN 0.0034965 0.0089815 -0.5191115 -2.724173 0 192 down
GSE9988_ANTI_TREM1_VS_ANTI_TREM1_AND_LPS_MONOCYTE_UP 0.0035088 0.0089815 -0.5178045 -2.721045 0 194 down 
fgp <- fgsea_plot(fgsea_res$res_msg, pathways_title='All signatures', condition_name='MT-CO1 low vs high')

kable(fgp)
pathway pval padj ES NES nMoreExtreme size state
GSE369_PRE_VS_POST_IL6_INJECTION_SOCS3_KO_LIVER_DN 0.0034722 0.0197796 -0.6451392 -3.367435 0 187 down
SHEN_SMARCA2_TARGETS_UP 0.0012563 0.0197796 0.6214452 3.217144 0 407 up
MILI_PSEUDOPODIA_HAPTOTAXIS_UP 0.0012255 0.0197796 0.6094541 3.181855 0 469 up
GSE9988_LPS_VS_VEHICLE_TREATED_MONOCYTE_DN 0.0035842 0.0197796 -0.6071365 -3.167430 0 191 down
chr16p11 0.0031056 0.0197796 -0.6427102 -3.161449 0 120 down
GSE9988_ANTI_TREM1_AND_LPS_VS_VEHICLE_TREATED_MONOCYTES_DN 0.0035211 0.0197796 -0.6003589 -3.138130 0 189 down
GSE9006_TYPE_1_VS_TYPE_2_DIABETES_PBMC_AT_DX_UP 0.0034722 0.0197796 -0.6005153 -3.134511 0 187 down
MT 0.0015949 0.0197796 0.9033591 3.126380 0 31 up
chr9q34 0.0036101 0.0197796 -0.5864285 -3.095703 0 210 down
GSE9988_ANTI_TREM1_VS_VEHICLE_TREATED_MONOCYTES_DN 0.0035088 0.0197796 -0.5900630 -3.083390 0 190 down
GSE9601_UNTREATED_VS_PI3K_INHIBITOR_TREATED_HCMV_INF_MONOCYTE_UP 0.0035587 0.0197796 -0.6029732 -3.079737 0 162 down
SENGUPTA_EBNA1_ANTICORRELATED 0.0032680 0.0197796 -0.6104509 -3.030616 0 132 down
chr22q11 0.0036765 0.0197796 -0.5603387 -2.967030 0 214 down
GSE6269_HEALTHY_VS_FLU_INF_PBMC_DN 0.0033113 0.0197796 -0.5834221 -2.963032 0 148 down
GSE36527_CD69_NEG_VS_POS_TREG_CD62L_LOS_KLRG1_NEG_DN 0.0035587 0.0197796 -0.5691509 -2.959361 0 183 down
GSE16385_MONOCYTE_VS_12H_IL4_TREATED_MACROPHAGE_DN 0.0035587 0.0197796 -0.5674304 -2.950415 0 183 down
GSE27670_BLIMP1_VS_LMP1_TRANSDUCED_GC_BCELL_UP 0.0035587 0.0197796 -0.5618871 -2.921592 0 183 down
GSE360_L_DONOVANI_VS_B_MALAYI_HIGH_DOSE_MAC_DN 0.0035714 0.0197796 -0.5614279 -2.916767 0 184 down
GSE360_DC_VS_MAC_B_MALAYI_HIGH_DOSE_DN 0.0035714 0.0197796 -0.5595859 -2.907197 0 184 down
QI_PLASMACYTOMA_UP 0.0036496 0.0197796 -0.5389177 -2.905090 0 243 down
GSE10325_LUPUS_BCELL_VS_LUPUS_MYELOID_DN 0.0035587 0.0197796 -0.5549483 -2.901693 0 192 down
TONKS_TARGETS_OF_RUNX1_RUNX1T1_FUSION_HSC_DN 0.0035088 0.0197796 -0.5585107 -2.891660 0 177 down
GSE22140_HEALTHY_VS_ARTHRITIC_GERMFREE_MOUSE_CD4_TCELL_DN 0.0035842 0.0197796 -0.5534128 -2.887153 0 191 down
GSE10325_BCELL_VS_MYELOID_DN 0.0035587 0.0197796 -0.5549508 -2.885526 0 183 down
GSE7218_UNSTIM_VS_ANTIGEN_STIM_THROUGH_IGG_BCELL_DN 0.0034364 0.0197796 -0.5660759 -2.884559 0 159 down
GSE9006_HEALTHY_VS_TYPE_2_DIABETES_PBMC_AT_DX_UP 0.0035842 0.0197796 -0.5568072 -2.883340 0 181 down
GSE23568_CTRL_TRANSDUCED_VS_WT_CD8_TCELL_DN 0.0034843 0.0197796 -0.5521093 -2.880758 0 188 down
GSE24634_TREG_VS_TCONV_POST_DAY10_IL4_CONVERSION_DN 0.0034843 0.0197796 -0.5485671 -2.862276 0 188 down
BASSO_CD40_SIGNALING_UP 0.0029674 0.0197796 -0.6003008 -2.857327 0 100 down
NIKOLSKY_BREAST_CANCER_16P13_AMPLICON 0.0030675 0.0197796 -0.5964448 -2.839071 0 105 down